Machine Learning Algorithms

Naive user-based systems

In this first scenario, we assume that we have a set of users represented by feature vectors:

Typical features are age, gender, interests, and so on. All of them must be encoded using one of the techniques discussed in the previous chapters (for example, they can be binarized). Moreover, we have a set of items:

Let's assume also that there is a relation which associates each user with a subset of items (bought or positively reviewed), items for which an explicit action or feedback has been performed:

In a user-based ...